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AI-Driven Border Modernization

Xolmirzayev Furqatbek MuxtarjonovichAlfraganus University, Tashkent, UzbekistanAbdusamatov AlisherTermez University of Economics and Service, Termez, UzbekistanR. N. RavikumarMarwadi University, Rajkot, IndiaJabbarov UmarbekS. AarthiMarwadi University, Rajkot, IndiaP. K. Mangaiyarkarasi
2026ng
ABI

Annotatsiya

This chapter examines how Artificial Intelligence is transforming customs operations through intelligent automation, predictive risk management, and paperless trade ecosystems. It highlights the limitations of traditional border processes manual paperwork, slow clearance, and fragmented data and explains how AI-driven tools such as machine learning, NLP, OCR, and IoT sensors improve accuracy, transparency, and security. The chapter also explores digital Single Window systems, blockchain verification, and interoperable data platforms that support faster and more reliable cross-border transactions. Case studies from the EU, ASEAN, and GCC regions demonstrate practical gains in efficiency and risk mitigation. Governance challenges including bias, cybersecurity, and data sovereignty are also discussed. The chapter concludes by emphasizing the need for ethical guidelines, regional cooperation, and future technologies such as quantum-AI and federated learning to build sustainable, secure, and next-generation trade corridors.

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